Quantitative Two-Layer Inversion and Customizable Sensor-Array Instrument for Electromagnetic Induction based Soil Conductivity Estimation

Electromagnetic (EM) measurement methods offer the great potential to non-invasively and contactlessly obtain geological and hydrological soil properties of the uppermost six meters of the subsurface with an areal resolution in the sub-meter range. The presented work is focused on small-sized frequency domain ‘electromagnetic induction’ (EMI) systems which combine the transmitter (Tx) and receiver (Rx) unit in one portable construction and obtain the apparent electrical conductivity (σa) of the sensed soil volume by inducing electrical currents and measuring the responding electromagnetic field. The sensing depth of EMI instruments depends on the sensor configuration and in particular the coil orientation and Tx–Rx separation. In principle, multi-configuration EMI data can be inverted for the electrical conductivity distribution over depth. However, there is a demand for efficient inversion algorithms and high-quality EMI data from different sensing depths to perform such an inversion. Here, a novel one-dimensional global-local inversion approach is implemented which evaluates the misfit between EMI data and forward modeled data for a two-layer soil using a L1-norm objective function. The global approach is based on a grid search for reasonable model parameters in combination with the local-sensitivity forward model. The two soil models with the smallest misfit are refined using the (local) simplex search algorithm with the more precise full solution electromagnetic forward model. The algorithm is analyzed using synthetic EMI data. Applying the inversion on quantitative EMI transect data from two commercial devices with eight different sensor configurations results in a two-layer electrical conductivity model with lateral and vertical conductivity changes that are in good agreement with a collocated electrical resistivity tomography data set. To improve the depth-resolution beyond available fixed configurations, a novel EMI prototype system (ElMa1) with customizable sensor-array is developed, containing multiple modular sensor units which can be flexibly arranged by the operator for each survey, ensuring optimal depth-sensitivity (i.e. coil orientations and Tx–Rx separations) for the specific investigation. The sensor units consist of coil-based transmitter and receiver circuits which allow for the measurement of the magnetic flux and the sensor impedance in a frequency range between 3 and 33 kHz, respectively. To allow for flexible sensor configurations, data processing and signal optimization, the transmitter current and the receiver voltages are separately digitized using 24-bit analog-to-digital converters (ADC’s) which provide a high dynamic range and phase stability. For a measurement time of 0.5 s, the ElMa1 system achieves an instrumental σa-accuracy of 1 mS/m at 20 kHz for the intended Tx–Rx separation of 1.0 m and an accuracy of 10 mS/m for a less favorable configuration with smaller Tx–Rx separation of 0.3 m and smaller measurement frequency of 5 kHz, both observed under stable temperature conditions. In addition, experimental data were corrected for temperature-induced system drifts by simulating the electrical circuit of the sensor system using spectral measurements

[1]  Evert Slob,et al.  Quantifying field-scale surface soil water content from proximal GPR signal inversion in the time domain , 2010 .

[2]  Egon Zimmermann,et al.  Development and drift-analysis of a modular electromagnetic induction system for shallow ground conductivity measurements , 2014 .

[3]  David J. Strauss,et al.  Spatial Prediction of Soil Salinity Using Electromagnetic Induction Techniques: 2. An Efficient Spatial Sampling Algorithm Suitable for Multiple Linear Regression Model Identification and Estimation , 1995 .

[4]  G. Keller,et al.  Frequency and transient soundings , 1983 .

[5]  J. Triantafilis,et al.  Hydrostratigraphic analysis of the Darling River valley (Australia) using electromagnetic induction data and a spatially constrained algorithm for quasi-three-dimensional electrical conductivity imaging , 2011 .

[6]  P. Hoekstra,et al.  Case Histories of Shallow Time Domain Electromagnetics in Environmental Site Assessment , 1992 .

[7]  F. A. Monteiro Santos,et al.  Resolving the spatial distribution of the true electrical conductivity with depth using EM38 and EM31 signal data and a laterally constrained inversion model , 2010 .

[8]  Harry Vereecken,et al.  Quantitative Two‐Layer Conductivity Inversion of Multi‐Configuration Electromagnetic Induction Measurements , 2011 .

[9]  J. Triantafilisa,et al.  Mapping clay content variation using electromagnetic induction techniques , 2005 .

[10]  A. Fraser-Smith,et al.  The Earth's electromagnetic environment , 2011 .

[11]  A. Beck,et al.  Assessment of the CMD Mini‐Explorer, a New Low‐frequency Multi‐coil Electromagnetic Device, for Archaeological Investigations , 2013 .

[12]  Marc Van Meirvenne,et al.  Evaluating the multiple coil configurations of the EM38DD and DUALEM‐21S sensors to detect archaeological anomalies , 2009 .

[13]  A. Christiansen,et al.  A review of helicopter‐borne electromagnetic methods for groundwater exploration , 2009 .

[14]  D. Corwin,et al.  Application of Soil Electrical Conductivity to Precision Agriculture , 2003 .

[15]  R. Aragüés,et al.  Mobile and georeferenced electromagnetic sensors and applications for salinity assessment. , 2008 .

[16]  S. Busch Full-waveform inversion of surface ground penetrating radar data and coupled hydrogeophysical inversion for soil hydraulic property estimation , 2013 .

[17]  D. R. Nielsen,et al.  Spatial Variability of Field‐measured Soil‐water Characteristics , 1985 .

[18]  Jan Vanderborght,et al.  Electromagnetic induction calibration using apparent electrical conductivity modelling based on electrical resistivity tomography , 2010 .

[19]  Jeffrey J. McDonnell,et al.  A new tool for hillslope hydrologists: spatially distributed groundwater level and soilwater content measured using electromagnetic induction , 2003 .

[20]  D. Corwin,et al.  Apparent soil electrical conductivity measurements in agriculture , 2005 .

[21]  Mark S. Seyfried,et al.  Geophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity , 2008 .

[22]  Roger Guérin,et al.  Interpretation of slingram conductivity mapping in near-surface geophysics: using a single parameter fitting with 1D model1 , 1996 .

[23]  Fernando A. Monteiro Santos,et al.  1-D laterally constrained inversion of EM34 profiling data , 2004 .

[24]  R. Gebbers,et al.  Electrical conductivity mapping for precision farming , 2009 .

[25]  N. Kitchen,et al.  Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture , 2001 .

[26]  Venkat Lakshmi,et al.  Advancing process‐based watershed hydrological research using near‐surface geophysics: a vision for, and review of, electrical and magnetic geophysical methods , 2008 .

[27]  Evert Slob,et al.  Coupling effects of two electric dipoles on an interface , 2002 .

[28]  P. Steerenberg,et al.  Targeting pathophysiological rhythms: prednisone chronotherapy shows sustained efficacy in rheumatoid arthritis. , 2010, Annals of the rheumatic diseases.

[29]  Bülent Tezkan,et al.  A Review Of Environmental Applications Of Quasi-Stationary Electromagnetic Techniques , 1999 .

[30]  Mohammad M. Islam,et al.  Depth slicing of multi-receiver EMI measurements to enhance the delineation of contrasting subsoil features , 2012 .

[31]  W. Amelung,et al.  Particulate Organic Matter at the Field Scale: Rapid Acquisition Using Mid-Infrared Spectroscopy , 2010 .

[32]  J. D. Mcneill Electromagnetic Terrain Conduc-tivity Measurement at Low Induction Numbers , 1980 .

[33]  Esben Auken,et al.  Layered and laterally constrained 2D inversion of resistivity data , 2004 .

[34]  L. Cockx,et al.  Comparing the EM38DD and DUALEM‐21S Sensors for Depth‐to‐Clay Mapping , 2009 .

[35]  J. D. Rhoades,et al.  Electrical Conductivity Methods for Measuring and Mapping Soil Salinity , 1993 .

[36]  G. E. Archie The electrical resistivity log as an aid in determining some reservoir characteristics , 1942 .

[37]  Jan M. H. Hendrickx,et al.  Inversion of Soil Conductivity Profiles from Electromagnetic Induction Measurements , 2002 .

[38]  I. J. Van Wesenbeeck,et al.  ESTIMATING SPATIAL VARIATIONS OF SOIL WATER CONTENT USING NONCONTACTING ELECTROMAGNETIC INDUCTIVE METHODS , 1988 .

[39]  P. M. van den Berg,et al.  An apparent‐resistivity concept for low‐frequency electromagnetic sounding techniques , 2000 .

[40]  Mohammad M. Islam,et al.  Mapping depth-to-clay using fitted multiple depth response curves of a proximal EMI sensor , 2011 .